correlations

• what is the difference between correlations and experiments

  experiments require manipulation of the IV and measurement of the resulting change in the DV.

  in a correlational study, no variables are manipulated, two co-variables are measured and compared to look for a relationship
• what are co-variables

  the two variables that are measured by the researcher and then compared to each other
• examples of co-variables

  age, height, IQ
• what is a scattergram


  a graph used to plot the measurements of two co-variables. they visually display the relationship between co-variables
• positive correlation


  as one co-variable increases, the other co-variable increases
• negative correlation

  as one co-variable increases, the other co-variable decreases
• how can the strength and direction of a correlation be described visually ?

  a scattergram
• how can the strength and direction of a correlation be described numerically?

  with a correlation coefficient
• correlation coefficient

  represents both the strength and direction of the relationship between the co-variables as a number between -1 and +1
• what correlation is considered to be strong

  0.8
• how are correlation coefficients calculated?

  using statistical tests such as Spearman's rho or Pearson's
• correlations strengths


  • correlational studies can highlight potential causal relationships, these can then be tested with experimental methods to discover cause and effect relationship
  • covariable data normally already exists and is accessible- few ethical issues in data collection
  • correlation coefficient is a useful tool in describing both the direction and strength of relationships between variables
• correlations weaknesses


  correlation does not show causation. A strong correlation may suggest a relationship exists between the two variables but it doesn't show which co-variable led to the change in the other co-variable and it is possible that an unknown third variable caused the change in both variables